most citedUniversal approximation of flows of control systems by recurrent neural networks

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eess.SY2023

Learning Flow Functions from Data with Applications to Nonlinear Oscillators

Miguel Aguiar, Amritam Das, Karl H. Johansson

We describe a recurrent neural network (RNN) based architecture to learn the flow function of a causal, time-invariant and continuous-time control system from trajectory data. By r…

eess.SY2023★ 1 cited

Universal approximation of flows of control systems by recurrent neural networks

Miguel Aguiar, Amritam Das, Karl H. Johansson

We consider the problem of approximating flow functions of continuous-time dynamical systems with inputs. It is well-known that continuous-time recurrent neural networks are univer…